In an effort to support my intellectual curiosities and union work, I’ve created this dashboard. The vast majority of this information comes from the KU Factsheets and Factbooks.
Continue reading “Quick Dashboard”Research on Gender and Promotion
In this post, I would like to do a follow-up on my previous blog on promotion. The following largely draws on various reports I have shared in different venues. Moreover, I had assistance from fellow sociologists and the KU-APSCUF Social Justice Committee in drafting various parts of those reports. As a social scientist, I believe that we should continuously gather and review this sort of data while addressing problems such as sexism within our institutions. I welcome any comments or criticism of the following information and analysis.
Overview
Promotion is a process that involves many actors both on and off-campus. This overview presents empirical data on gender and promotion at Kutztown University. Gender, much like race and sexuality, undoubtedly impact promotion. The data presented is meant to provide context as to what is going on at the university. Clearly, gender matters. However, the following can give us insight as to how it matters at Kutztown University. That said, the following cannot speak to individual cases of promotion or denial. It can, however, speak to structural flaws at KU in regard to promotion, as well as issues in higher education.
Using Factsheets and Factbooks from the Office of Institutional Research (OIR), we see that there are significant gaps between male and female professors at different ranks. *** Note: I am using OIR data that only uses “men” and “women” as categories. Figure 1 illustrates the number of men and women at different ranks from 2007-2019. It should be stated here that the overall number of faculty has decreased in this period as well. That said, Figure 2 shows a gradual increase in the percentage of female assistant professors. From 2007-2009, there were more male assistant professors than female. Since 2009, there have been more women at the assistant professor rank. Notably, in 2019, we see about twice as many women at assistant than men.
This suggests that KU has been hiring more women than men – while overall staffing is decreasing. Despite these gains, there are still significantly more male associate and full professors, than women at the same rank. In fact, the gap between male and female associate professors has increased since 2016 despite gains a few years earlier. In 2016, 46.1% of associate professors were women, and in 2019, it had dropped to 41.7%. The percentage of women at full professor rank dropped as well. This suggests a step backward.
Figure 2 illustrates that some women are getting promoted to full professor. More on that later. However, we see a decline in associate professors that parallels gains in the rank of full professor. Yet, given the number of female assistant professors, we should be seeing the percentage of associate professors hold or even increase if they are being promoted at the same rate as men.
We see this in greater detail in Figure 3, which illustrates the number of male and female tenured assistant professors. In our system this is possible. There are two observations that can be made here. The first is there is nearly 3 times the number of women than men that are tenured assistant professors. The second is that while the number of tenured male assistant professors has decreased, overall the number of women has largely remained steady – despite an increase in the middle of this time period.
The Promotion Process
We are a unionized campus, as such our promotion process is governed by our collective bargaining agreement, as well as a local set of guidelines. Looking at the data provided to the faculty union (APSCUF) by the administration, and generated by past university promotion committee (UPC) members, we see that men and women are being promoted at relatively similar rates between 2010-2018. On the surface, this may appear to be a contradiction. What this suggests is a major part of the bias/discrimination that is occurring has a structural dimension.
First, while promotion rates are similar, men are generally applying for a promotion at higher rates than women for both associate and full professors ranks. For instance, more men applied for associate professor 2016-2018, despite there being more women assistant professors. In other words, men are applying at higher rates than women. We need to ask why this is the case. Is it due to maternity leave, women being discouraged from applying, or lack of mentorship?
Second, related to the question about mentorship, the department where female assistant professors are in could be variable. For instance, a single department – Elementary Education – in Fall 2019 had 7 tenured assistant professors. Which accounts for 19% of the 37 tenured assistant professors in 2019. All are women. Another department, English has 5 tenured assistant professors, most of which are women. These two departments account for about 1/3 of all tenured assistant professors. This could be an internal departmental problem, a broader disciplinary issue tied to norms in publishing, or how fields are gendered .
My previous blog entry examined Google Scholar results for successful promotion applicants. Looking at results in Google Scholar (which is not the same as publications), I found that in the College of Liberal Arts & Sciences (CLAS) between 2010-2018 the following:
- For promotion to Associate Professor for those in Humanities fields, there was a mean of 2.06 results. For the Social Sciences there was an average of 3 results, and for STEM fields an average 3.97.
- For promotion to Full Professor in CLAS, we see means of 4.85 for Humanities, 11.63 for Social Sciences, and 10.57 for STEM.
The difference in disciplines is interesting here. It is perhaps worth asking if issues are perhaps exacerbated in fields where there is less “traditional” research activity such as peer-reviewed publications, or disciplines that are heavily gendered such as education. Here, it is also important to ask how these expectations affect men and women differently.
Below is an updated table with promotion to full professor data (the differences between this chart and the previous blog are due to my catching some errors).
Figure 4: Google Scholar Results of Promotion Applicants to Full
| Year | # Promo. to Full | MEAN Google Scholar Results (All Years Prior to Promo) | Median Google Scholar Results |
| 2010 | 7 | 6.28 | 7 |
| 2011 | 5 | 6.66 | 7 |
| 2012 | 1 | 2 | 2 |
| 2013 | 5 | 4.5 | 3.5 |
| 2014 | 5 | 12.4 | 13 |
| 2015 | 10 | 3.64 | 1.5 |
| 2016 | 13 | 5.9 | 4 |
| 2017 | 16 | 12.37 | 6 |
| 2018 | 6 | 10.83 | 12 |
| 2019 | 10 | 5.8 | 5 |
| 2020 | 14 | 7.29 | 6 |
| 2021 | 7 | 6.14 | 5 |
| All | 99 | 7.2 | 5.0 |
A claim commonly made about promotion at Kutztown (and beyond) is escalating requirements. That said, there does not seem to be a steady increase in Google Scholar results over time. Rather, there has been a lot of fluctuation. Again, the data above is simply a count of search “hits” with a successful applicant’s name. It does not take into consideration “quality” of item that is found. It is a fact, that there has been greater scrutiny of publications since 2015, following a crackdown on faculty publishing in predatory journals.
Given the growing importance of quality (perhaps in addition to quantity), this raises the question of time between promotions. Since my previous blog post, I’ve been able to get more complete data for recently promoted faculty As such, I have since been able to look up the data found in Figure 6. As you can see, there’s a great deal more variation among successful female applicants for full professor than for men.
Intersectionality
Figure 6 may imply an age dimension for women going up for full professor. This also means that other factors should be looked at. I was unable to do a thorough analysis for women of color. As seen in Figure 7, KU is not a particularly diverse campus. To put this in perspective, only 9.4% of faculty are women of color. The incredibly small numbers, especially for Black and Latinx women, make it difficult to see larger trends. However, we do see that Black women at KU generate above-average Google Scholar results. Specifically, the 8 black women as of Fall 2019 at KU (1 full professor, 2 associate professors, and 5 assistant professors) had a mean of 4.6 results and a median of 2.5.
Figure 7: Faculty Demographics (Fall 2019)
| Male | Female | Total | |
| White | 193 | 183 | 376 |
| African-American | 10 | 8 | 18 |
| Hispanic | 9 | 7 | 16 |
| Asian/Pacific Islander | 22 | 21 | 43 |
| Native American | 1 | 1 | 2 |
| 2 or More Races / Unknown | 5 | 7 | 12 |
| Total | 240 | 227 | 467 |
Conclusion
Wrapping up, promotion is a process. It is not just a matter of a decision being made in a fixed point in time. Rather, there are a number of social/political/cultural forces and biases that influence the outcome. It is my hope that this blog post assists others in having a meaningful conversation as to how to mitigate those biases.
Devaluing Instruction
It’s no secret that higher education is not just underfunded, but increasingly so. Administrators have a habit of saying personnel costs (especially faculty salaries) are undermining university finances. Yet, while personnel costs matter, we see that such expenses represent a smaller and smaller percentage of overall costs at institutions in the PASSHE system.
Continue reading “Devaluing Instruction”The Tragedy of the Commons
Previously, I blogged about efficiency in our system having a potentially racist dimension (see: Tenner, 2018). One of the consequences of the efficiency push is that libraries are under threat. There is a chance one or more campuses could not have a library and/or any librarians due to cuts. There are going to be some real serious academic and social consequences to this. In sociologist Eric Klinenberg’s Palaces for the People (2018), libraries are examples of social infrastructure – the physical places and entities that have a direct impact on how people. As Klinenberg points out: “Social infrastructures that promote efficiency tend to discourage interaction and the formation of strong ties.” (p. 18). One of the things administrators fail to understand is that libraries do many things. They are community centers, meeting spaces, places to study, and more. They provide jobs for student workers (which I had as an undergrad). They can even house coffee shops, where people get together. Libraries can be safe spaces for homeless students. This is in addition to their being hubs of academic activity for faculty, students, and the wider community.
Our administrators argue that “library services” will still exist. Yet, they have no plan of what that might mean. We cannot disconnect those “services” from the social and physical dimensions of university libraries. That includes the integral nature of librarians in providing those services. Take, for instance, the transition of libraries into “information commons” in recent years. Key here is the idea that they are “commons.” Again, they are places where students can work together, with librarians, or faculty for a variety of different projects.
In sum, the destruction of libraries in PASSHE would be a true “tragedy of the commons.”
Efficiency isn’t necessary Efficient in HigherEd
Here’s a follow up to my previous post about student-to-faculty ratios not being related to university finances. I recently asked an administrator if the ratio is a proxy for revenues and expenditures. I was told that the ratio is actually a measure of efficiency.
For my more critical readers, I can hear the groans upon hearing the word “efficiency.” No doubt efficiency is a very corporate term and a stand-in for return on investment. Stepping aside from the very corporate dimensions of that word, efficiency also refers to the relationship between inputs (e.g. resources) to outputs (e.g. a task or function). For example, efficiency can be reducing the amount of energy needed to light up a house. Yet, even from a technical standpoint, efficiency is full of contradictions. Jevon’s Paradox occurs when improvements in energy efficiency lead to more consumption. This increased consumption offsets the potential benefits of “efficiency.” In other words, the technocratic push for efficiency often ignores the real-world deployment of such tools and strategies.
Real-world consequences can be relatively minor like leaving your lights on more since you have energy-efficient bulbs. However, the push for efficiency has had negative consequences in other ways. Edward Tenner (2018) has written about the Efficiency Paradox, noting that efficiency is rooted as much in “racism and xenophobia as in technological idealism” (xii). The reason being efficiency often comes from the top without regard to the social consequences of deploying formulas to optimize whatever those in power want to make efficient. For example, metrics to optimize “safety” can lead to segregation and discrimination in mortgage lending.
What does this mean in education? Is a faculty member teaching more students per class more efficient? Well if efficient means cheaper, then yes. However, what sort of consequences come with that? Retention and graduation rates come to mind. This is especially going to be costly for first-generation, those with disabilities, LGBTQ, non-traditional, and students of color. They need a diverse faculty who can provide mentorship and a safe space for them throughout their careers. As such, an efficiency metric solely based on increasing class sizes might not solve the financial problems caused by decreased enrollment. Then, of course, we are now in the world of COVID-19. Larger classes can limit options for physical distancing.
I conclude with this final thought on metrics. Our system has other metrics for financial sustainability they are not using. For instance, they have “Education and General (E&G) Expenditures per Student FTE.” This is a bit better since we are back to talking about actual finances. However, there’s a political component. When they propose they are increasing the student-to-faculty ratio, they are saying they want to spend less per student. This E&G metric would confirm that. The optics here are very different than suggesting a ratio of 20:1. I believe that this is why they chose this problematic student-to-faculty metric, versus more accurate ones for examining financial sustainability.
Criticizing Student-to-Faculty Ratios
There are a lot of metrics or methods of measuring what we do in higher education. An important one for us professors is faculty full-time equivalent (FTE), which is a percentage calculation of a single faculty member’s teaching. In other words, an FTE of 1.0 represents a full-time professor. Two people hired half-time would also be 1.0. At my institution and system, it is primarily based on teaching load. In my case, teaching my full 4/4 load is represented as 1.0 in a spreadsheet. In that spreadsheet, there is also a tally of all faculty to get an overall number of faculty FTE, which is 428.61 for Fall 2019. This is also done for students and staff as well as using other formulas for measuring the notion of full-time.
Continue reading “Criticizing Student-to-Faculty Ratios”Overworked (the pandemic version)
Previously, I’ve written about my workload. As I begin to prepare for Fall 2020, I’ve been thinking about how I can design classes that will avoid the COVID chaos of Spring 2020.
Like everyone else, my time commitment to my classes increased dramatically once we went online due to the COVID-19 closures and quarantine in the spring. In addition to all the work needed to convert my face-to-face classes online, there were other issues. Rather than have a relatively set schedule for work, we moved into a 24/7 environment that has broken apart our already porous academic work and non-academic lives.
Continue reading “Overworked (the pandemic version)”Persistence in Academic Publishing
As we close out 2019, I’ve been reflecting a lot on the fact that it’s been ten years since I earned my Ph.D. Things are good for me. I’m lucky and privileged to be a full professor with tenure. This journey, however, wasn’t easy. Academia is like a series of races, where you’re often crawling past a finish line dehydrated and glad it’s over. Take for instance publishing. I just had an article come out that took five years to get published. I also had another recent article that took six years. This means rejection after rejection, a lot of negative feedback from reviewers, as well as the purgatory of several revise and resubmits. Sure, I have a writing strategy. However, there’s no way to really anticipate or plan for the inevitable heartbreak of being rejected after a third round of R&Rs. My point in bringing this up is to emphasize that writing, especially academic writing, is difficult. It’s hard practically, intellectually, as well as emotionally.
So here are some thoughts:
- As people have started doing on Twitter, we should normalize rejection. There are two parts to his. The first is we need to demystify the process of academic writing and publishing. This means openly talking about the journey from the data, the field, or wherever, to the article or book. The second part is honestly talking about the stumbles, so we have a culture that reinforces the idea that rejection is not the same as failure.
- Another part of this involves understanding that there are different audiences out there for different work. Unfortunately, this might mean that you end up with a reviewer (or editor) who simply disagrees with your approach. So, the rejection isn’t about you or your work. Real story: I once had minor R&R. However, when I resubmitted it, it went to an incoming editor who disagreed with my approach and desk-rejected it.
- Yet, that doesn’t mean that your work is perfect. Really, no one’s work is perfect. This means one has to understand the difference between constructive criticism, and someone being a jerk. For a great discussion of this, check out his episode of the SocAnnex podcast on “Academic Hazing.”
Wrapping this post up (and closing out the decade), it will be interesting to see how academic work changes in the next ten years.
Faculty Diversity & Hiring
In a previous post, I had indicated that more diverse departments (social sciences, math, and business) generally have an above average number of students per term. In this post, I want to discuss issues in diversifying faculty. Why? My faculty union recently tweeted this image
While the expression of solidarity with fellow academics is important, the optics of the image is just plain bad. The lack of racial and ethnic diversity in the photo is real problem. One long-time union leader indicated to me that this is a long-standing problem with our organization.
In this post, I would like to look at how lack of diversity happens – at least on my campus. While administration gives departments lines, it is ultimately up to departments to put in the effort (if that’s what they really want to do) and hire more faculty of color. At the same time, faculty searches are complicated. It is hard to say exactly why a single search turned out the way that it did. However, we can see patterns across multiple searches. So here is my analysis of faculty hiring and diversity in my College of Liberal Arts and Sciences using available data.
Using the College’s annual newsletter, I looked at new tenure track hires (or temporary conversions) between 2012 and 2018. In this 7-year period of time 12 out of 15 departments gained tenured track faculty. I’m using the term “gained tenured track” rather than hire, because – I estimate – a large number of these professors were temporary/adjunct faculty at one point. I have also chosen to obscure the names of the departments to reduce blowback. However, I suspect it is pretty easy to decipher which department is which if one really wants to find out.
Table 1: New Tenure Track Faculty 2012-2019
|
Dept
|
# TT
|
|
A
|
9
|
|
B
|
4
|
|
C
|
3
|
|
D
|
2
|
|
E
|
4
|
|
F
|
3
|
|
G
|
4
|
|
H
|
4
|
|
I
|
2
|
|
J
|
2
|
|
K
|
1
|
|
L
|
1
|
In addition, I looked at data from our Office of Institutional Research, and found that all staffing (including secretaries, faculty and administration) in the CLAS is 79.8% white. Then looked at the demographics of the 12 departments that gained a tenure track faculty member. Below in Figures 2a, b, c you can see the number of faculty/staff of color, overall department size, and percentage faculty/staff of color (or those who didn’t identify as white).
Table 2a: 2012 & 2019 Department Demographics
|
Department
|
A
|
B
|
C
|
D
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
1
|
35
|
2.9%
|
7
|
22
|
31.8%
|
6
|
14
|
42.9%
|
2
|
13
|
15.4%
|
|
FALL
|
4
|
42
|
9.5%
|
8
|
27
|
29.6%
|
4
|
12
|
33.3%
|
2
|
13
|
15.4%
|
Table 2b: 2012 & 2019 Department Demographics
|
Department
|
E
|
F
|
G
|
H
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
6
|
21
|
28.6%
|
1
|
8
|
12.5%
|
5
|
14
|
35.7%
|
2
|
19
|
10.5%
|
|
FALL
|
4
|
14
|
28.6%
|
0
|
9
|
0.0%
|
3
|
11
|
27.3%
|
3
|
21
|
14.3%
|
Table 2c: 2012 & 2019 Department Demographics
|
Department
|
I
|
J
|
K
|
L
|
||||||||
|
|
# Faculty of Color
|
Dept
|
% Faculty of Color
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
# FoC
|
Dept
|
% FoC
|
|
FALL
|
3
|
25
|
12.0%
|
3
|
17
|
17.6%
|
6
|
15
|
40.0%
|
1
|
13
|
7.7%
|
|
FALL
|
3
|
26
|
11.5%
|
3
|
21
|
14.3%
|
7
|
20
|
35.0%
|
1
|
16
|
6.3%
|
From Table 1 it is clear that hiring is incredibly uneven. Department A gained 9 tenure track faculty in a 7-year period of time. 9 out of 39 new tenure track faculty in this period of time, or 23% of new faculty in the college joined Department A. In terms of diversifying the university, it can be argued that this department was given more opportunities to recruit faculty than any other department in our college. Yet, this department – which was not particularly diverse – actually became less diverse over time as seen in Table 2a.
At the same time, we also see departments that do not receive many (or any) lines are not likely to become diverse. For instance, Department L only had 1 hire/conversation. While this department is pretty homogenous, they have had far fewer opportunities to diversify. This may be obvious, but it is clear some departments have greater power to change than others.
While other departments received fewer new tenure track faculty, there are some interesting observations to be made. For instance, we can look at Department F, that had zero faculty of color and managed to recruit someone of color in one of their 3 searches/conversions.
Put another way, decisions made by Department A have wide ranging implications for faculty demographics. Blame might not be the right word, but they perhaps have a greater responsibility to think about the bigger picture. Departments that get lines, especially those that get repeat opportunities can dramatically change the campus climate for faculty of color. To put this into perspective, about 21.7% of our 479 faculty aren’t white. There were only 16 Black, 24 Latinx, and 48 Asian faculty members in Fall 2018. Given how low these numbers are, every new hire of a scholar of color is significant.
How do we explain Department A?
I do think it is worth noting that, according to the 2017 Survey of Earned Doctorates, US citizens and permanent residents in his area of study are 79.3% white. This is also a field in which people do study communities of color and their culture. So, I have no doubt there are those who recognize the problem. This issue is likely due to 1) specific area of search and existing faculty interests 2) our geographic location 3) the way in which people are biased toward those that look the same, or come from similar backgrounds. The question, however, is whether people who realize there is a problem are willing to challenge the status quo, and be more creative in running searches. This also requires administration to help departments try new models of hiring. This is something other institutions have effectively done.
Consequences
There are a lot of consequences, but I want to focus primarily on university service such as involvement in the union. While large departments have downsides, a plus side is that workload can be spread out over more faculty. This includes department-level work, but also university-wide service. Politically, this can have consequences. Representation in our local union’s representative assembly is based on department size. In addition, large departments have an easier time having gaining additional representation through elected leaders in various “shared governance” bodies.
For existing faculty of color, this means more work. It is well documented that faculty of color do a lot of “invisible labor” through their service activities. Again, with so few black and Latinx faculty, individuals are repeatedly being ask to do more and more work.
In conclusion, I suspect if I were to look at data for other large departments in other colleges at my university, I may see something similar. Again, I would like to emphasize that large departments that receive lines have greater responsibility to the campus community to critically examine their search procedures.
Some data on promotion at my university
In this blog post, I would like to provide some data for my colleagues on promotion at our university. I have heard many different comments in regards to research and publications. However, there appears to be very little data, or evidence beyond anecdotes describing what’s going on systematically. So, I’ve sat down and put this estimate together. The following chart of search “results” for publications was created using our Daily Brief newsletter announcements, and doing searches on Google Scholar.
| Assistant-Associate Professor | Associate-Full Professor | |||||
| Year | # Promoted to Associate | MEAN Results
(Prior 5 Years) |
Median | # Promoted to Full | MEAN Results
(All Years Prior) |
Median |
| 2010 | 11 | 2.45 | 1.00 | 7 | 6.28 | 7.00 |
| 2011 | 16 | 3.00 | 2.00 | 5 | 6.66 | 7.00 |
| 2012 | 14 | 2.00 | 1.00 | 1 | 2.00 | 2.00 |
| 2013 | 19 | 2.00 | 1.00 | 5 | 4.50 | 3.50 |
| 2014 | 19 | 4.00 | 2.00 | 5 | 12.40 | 13.00 |
| 2015 | 19 | 2.00 | 1.00 | 10 | 3.64 | 1.50 |
| 2016 | 14 | 2.43 | 1.00 | 13 | 5.90 | 4.00 |
| 2017 | 13 | 2.23 | 1.00 | 16 | 12.37 | 6.00 |
| 2018 | 13 | 2.69 | 3.00 | 6 | 10.83 | 12.00 |
| All | 2.40 | 1.00 | 7.86 | 6.00 | ||
These numbers should be considered estimates, for the following reasons:
- Promotion is not only linked to “Scholarly Growth” per our union contract. It includes teaching and service. The numbers to not necessarily suggest a “minimum” needed for promotion.
- The above only includes those listed in the Daily Brief, and does not include those who were later promoted through a union grievance, or lawsuit.
- Google Scholar under-indexes the humanities, and of-course those in the arts might be in fields where one doesn’t publish to gain tenure or promotion. Also, as publishers put more past material online, sometimes these numbers change.
- Google Scholar results used are simple counts. There is no differentiation between books or articles. However, our union contract explicitly states that the evaluation process should use quality over quantity.
- At the same time, it should be noted that Google Scholar counts also include book reviews, non-peer reviewed reports, as well as publications in predatory journals. However, it should be noted that there was not a concern regarding predatory publications by our university administration until 2016.
- It is important to note that our system separates tenure and promotion to associate professors. This means it is possible to receive tenure and be denied promotion to associate professor. It also means someone can choose not to apply for promotion. Nonetheless, for convenience, I have used results in the 5 years leading up to promotion, which is time time-frame when most faculty will also be applying for tenure. However, in several cases people took longer than 5 years to be promoted to associate.
- For data on full professors, I’ve chosen to use lifetime results prior to the year in which the individual was promoted. The range in which people on our campus become full professors range from 3 years, to decades, after they receive promotion to associate. Without direct access to everyone’s CVs, it’s really hard to come up with a perfect way to delimit time-to-full.
In the absence of looking at actual publications (not just results) and creating a more nuanced coding system, I did look at disciplinary fields, and academic unit/college. For instance, our College of Liberal Arts & Sciences (CLAS) is where most of the traditional “research” fields within the humanities, social sciences, and STEM are located. Looking at that breakdown, we see for promotion to Associate Professor for those in Humanities fields, there was a mean of 2.06 results. For the Social Sciences there was an average of 3 results, and for STEM fields an average 3.97. For promotion to Full Professor in CLAS, we see means of 4.85 for Humanities, 11.63 for Social Sciences, and 10.57 for STEM.
Finally, below is data from our Office of Institutional Research regarding faculty ranks.